The Temporal Perspective in Higher Education Learners: Comparisons between Online and Onsite Learning

Open access

Abstract

Higher Education increases flexibility with online learning solutions. Nevertheless, dropout rates in online university are large. Among the reasons, one aspect deserving further study is students’ Time Perspective (TP), which has been studied in onsite HE. It is necessary to know the TP profile of the growing population of online students, and consider its relation with students’ preference and convenience factors for choosing online or onsite contexts. In this study, learners’ TP in an online and an onsite Catalan HE institutions are compared. Results show that HE students present a high future orientation in general, while online students showed a higher orientation to past negativism. Basic guides are given to help institutions and students in the choice of the better suited learning context according to their TP.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • 1. Altbach P.; Reisberg L. and Rumbley L. (2009). Trends in global higher education: Tracking an academic revolution. Chestnut Hill MA: Boston College Center for International Higher Education.

  • 2. Artino A.R. (2010). Internet and Higher Education Online or face-to-face learning? Exploring the personal factors that predict students’ choice of instructional format. In The Internet and Higher Education 13(4) (pp. 272-276).

  • 3. Bates A.T. (2004). Technology e-learning and distance education. Routledge.

  • 4. Bishop M.J.; Hyclak T. and Yerk-Zwicki S. (2007). The clipper project: Lessons learned teaching an online economics course. In Journal of Computing in Higher Education 18(2) (pp. 99-120).

  • 5. Boeren E.; Nicaise I.; Baert H. (2010). Theoretical models of participation in adult education: The need for an integrated model. In International journal of lifelong education 29(1) (pp. 45-61).

  • 6. Bonk C.J. (2009). The world is open: How web technology is revolutionizing education. Jossey-Bass

  • 7. Bosato G. (2001). Time perspective academic motivation and procrastination. Master’s thesis. San Jose State University.

  • 8. Carnoy M.; Jarillo B.; Castano-Munoz J.; Duart J.M.; Sancho-Vinuesa T. (2012). Who attends and completes virtual universities: the case of the open University of Catalonia (UOC). In Higher Education 63 (pp. 53-82).

  • 9. Clay M.; Rowland S. and Packard A. (2009). Improving undergraduate online retention through gated advisement and redundant communication. In Journal of college student retention 10(1) (pp. 93-102).

  • 10. Clayton K.; Blumberg F. and Auld D.P. (2010). The relationship between motivation learning strategies and choice of environment whether traditional or including an online component. In British Journal of Educational Technology 41(3) (pp. 349-364).

  • 11. Cocea M. and Weibelzahl S. (2011). Disengagement Detection in Online Learning: Validation Studies and Perspectives. In IEEE transactions on learning technologies 4(2) (pp. 114-124).

  • 12. Collier C. and Morse F.K. (2002). Requiring independent learners to collaborate: Redesign of an online course. In Journal of Interactive Online Learning 1(1) (pp. 1-9).

  • 13. Concannon F.; Flynn A. and Campbell M.(2005). What campus-based students think about the quality and benefits of e-learning. In British Journal of Educational Technology 36(3) (pp. 501-512).

  • 14. Costa P. and McCrae R. (1992). NEO personality inventory-revised (NEO PI-R). Odessa FA: Psychological Assessment Resources.

  • 15. Cuthrell K. and Lyon A. (2007). Instructional strategies: What do online students prefer? In MERLOT Journal of Online Learning and Teaching 4 (pp. 357-362).

  • 16. Dabbagh N. (2005). Pedagogical models for E-Learning: A theory-based design framework.In International Journal of Technology in Teaching and Learning 1(1) (pp. 25-44).

  • 17. Daugherty M. and Funke B.L. (2007). University faculty and student perceptions of webbased instruction. In The Journal of Distance Education 13(1) (pp. 21-39). Retrieved from http://www.jofde.ca/index.php/jde/article/viewArticle/134

  • 18. de Bilde J.; Vansteenkiste M. and Lens W. (2011). Understanding the association between future time perspective and self-regulated learning through the lens of self-determination theory. In Learning and Instruction 21(3) (pp. 332-344).

  • 19. de Volder M.L. and Lens W. (1982). Academic Achievement and Future Time Perspective as a Cognitive-Motivational Concept. In Journal of Personality and Social Psychology 42(3) (pp. 566-571).

  • 20. Deal III W. (2002). Distance Learning: Teaching technology online. In The Technology Teacher 61 (pp. 21-26).

  • 21. Delfino M.; Manca S.; Persico D.; Sarti L. (2004). Online Learning: Attitudes Expectations and Prejudices of Adult Novices. In Proceedings of the IASTED Web Based Education Conference Innsbruck Austria (pp. 31-36).

  • 22. Diaz D. (2002). As distance education comes of age the challenge is keeping the students. In Chronicle of Higher Education (p. A39).

  • 23. Diaz D.P. and Cartnal R.B. (1999). Students’ Learning Styles in Two Classes and Equivalent On-Campus. In College teaching 47(4) (pp. 130-135).

  • 24. Díaz-Morales J. F. (2006). Estructura factorial y fiabilidad del Inventario de Perspectiva Temporal de Zimbardo. In Psicothema 18(3) (pp. 565-571).

  • 25. Eren A. (2009). Exploring the effects of changes in future time perspective and perceived instrumentality on graded performance. In Electronic Journal of Educational Research 19(7) (pp. 1217-1248).

  • 26. Evans T.N. (2009). An investigative study of factors that influence the retention rates in online programs at selected state state-affiliated and private universities. PhD Dissertation. UMI Number: 3388741.ProQuest.

  • 27. Favretto G.; Caramia G. and Guardini M. (2005). E-learning measurement of the learning differences between traditional lessons and online lessons. In European Journal of Open Distance and e-Learning 8(2). Available online at: http://www.eurodl.org/index.php?p=archives&year=2005&halfyear=2&article=187

  • 28. Fillion G.; Limayem M.; Laferrière T. and Robert M. (2007). Integrating ICT into higher education: a study of onsite vs. online students. In Academy of Educational Leadership Journal 11(2).

  • 29. Fischer G.; Rohde M. and Wulf W. (2007). Community-based learning: The core competency of residential research-based universities. In Computer-Supported Collaborative Learning 2 (pp. 9-40).

  • 30. Fourez M. (2009). Impoverished students’ perspectives of time. ProQuest Dissertations and Theses.

  • 31. Gallagher J.G. (2007). Online Learning: Strategy or Sophistry? In European Journal of Open Distance and E-Learning 10(1). Available online at: http://www.eurodl.org/index.php?p=archives&year=2007&halfyear=1&article=257

  • 32. Gibbs G. (2003). The future of student retention in open and distance learning. In The future of open and distance learning (pp. 37-48).

  • 33. Gilbert N. (2001). Researching Social Life. SAGE.

  • 34. Glenn M. and D’Agostino D. (2008). The Future of Higher Education: How Technology Will Shape Learning. New Media Consortium 2008 October 1. ERIC Document Reproduction Service No. ED505103. Retrieved February 19 2014 from ERIC database.

  • 35. Glover L. and Lewis V. (2012). Student preference online versus traditional courses. In The Global eLearning Journal 1(3) (pp. 1-28).

  • 36. Green K.C. (1996). The coming ubiquity of information technology. In Change: The Magazine of Higher Learning 28(2) (pp. 24-28).

  • 37. Halsne A.M. and Gatta L.A. (2002). Online versus Traditionally-Delivered Instruction: A Descriptive Study of Learner Characteristics in a Community College Setting. In Online Journal of Distance Learning Administration 5(1) (p. 1).

  • 38. Harrington R. and Loffredo D.A. (2010). MBTI personality type and other factors that relate to preference for online versus face-to-face instruction. In The Internet and Higher Education 13 (pp. 89-95).

  • 39. Hiltz S.R.; Coppola N.; Rotter N.; Toroff M.; Benbunan-Fich R. (2000). Measuring the Importance of Collaborative Learning for the Effectiveness of ALN: A Multi-Measure. In J.Bourne (ed.) Online Education: Learning effectiveness and faculty satisfaction: Volume 1. (p. 101-119).Needham MA.: Sloan-C.

  • 40. Horstmanshof L. and Zimitat C. (2007). Future time orientation predicts academic engagement among first-year university students. In British Journal of Educational Psychology 77(3) (pp. 703-718).

  • 41. Hu S.; Katherine L. and Kuh G.D. (2011). Student typologies in higher education. In New Directions for Institutional Research (pp. 5-15)

  • 42. Jacobs J. and King R.B. (2002). Age and college completion: A life-history analysis of women aged 15-44. In Sociology of Education 75 (pp. 211-230).

  • 43. Karber D. (2003). Comparisons and contrasts in traditional versus online teaching in management. In Higher Education in Europe 26 (pp. 533-536).

  • 44. Kell C. (2006). Undergraduates’ learning profile development: what is happening to the men? In Medical Teacher 28(1) (pp. 16-24).

  • 45. Kim T.; Welch S.M.; Nam S. (2012). Examining Graduate Students’ Perceptions of and Preferences for Online Courses. In proceedings of Academic and Business Research Institute International Conference - Las Vegas 2012 October 4 - 6 2012. Available online at: http://www.aabri.com/LV2012Manuscripts/LV12065.pdf

  • 46. Koons K. (2012). New study - students prefer online college classes to traditional classes.

  • 47. Lee Y.; Choi J. and Kim T. (2012). Discriminating factors between completers of and dropouts from online learning courses. In British Journal of Educational Technology 44(2) (pp. 328-337). doi:10.1111/j.1467-8535.2012.01306.x

  • 48. Leidner D.E. and Jarvenpaa S.L. (1995). The use of information technology to enhance management school education: a theoretical view. In MIS Quarterly 19(3) (pp. 265-91).

  • 49. Lens W.; Simons J. and Dewitte S. (2001). Student motivation and self-regulation as a function of future time perspective and perceived instrumentality Motivation in learning contexts: Theoretical advances and methodological implications (pp. 233-248) Pergamon: New York.

  • 50. MacGregor C.J. (2000). Does personality matter? A comparison of student experiences in traditional and online classrooms. In Dissertation Abstracts International 61 1696A.

  • 51. Malka A. and Covington M. V. (2005). Perceiving school performance as instrumental to future attainment: effects on graded performance. In Contemporary Educational Psychology 30(1) (pp. 60-80).

  • 52. Mello Z.R. and Worrell F.C. (2006). The Relationship of Time Perspective to Age Gender and Academic Achievement among Academically Talented Adolescents. In Journal for the Education of the Gifted 29(3) (pp. 271-289).

  • 53. Miller R.B. and Brickman S.J. (2004). A model of future-oriented motivation and selfregulation: effects of time perspective on student motivation. In Educational Psychology Review 16(1) (pp. 9-33).

  • 54. Mortagy Y. and Boghikian-Whitby S. (2010). A longitudinal comparative study of student perceptions in online education. In Interdisciplinary Journal of E-Learning and Learning Objects 6(1) (pp. 23-44).

  • 55. Northrup P. (2002). Online learners’ preferences for interaction. In The Quarterly Review of Distance Education 3(2) (pp. 219-226).

  • 56. Oppedisano V. (2011). The (adverse) effects of expanding higher education: Evidence from Italy. In Economics of Education Review 30(12).

  • 57. Paechter M. and Maier B. (2010). Online or face-to-face? Students’ experiences and preferences in e-learning. In The Internet and Higher Education 13(4) (pp. 292-297).

  • 58. Palloff R.M. and Pratt K. (2003). The virtual student: A profile and guide to working with online learners. Jossey-Bass.

  • 59. Paunescu M. (2013). Students’ Attitudes towards Technology-Enabled Learning: A Change in Learning Patterns? The Case of a Master’s Course in Political Science. In European Journal of Open and Distance e-Learning 16(1). Available online at: http://www.eurodl.org/index.php?p=archives&year=2013&halfyear=1&article=554

  • 60. Peetsma T.T.D. (2000). Future time perspective as a predictor of school investment. In Scandinavian Journal of Educational Research 44(2) (pp. 177-192).

  • 61. Pérez-Cereijo M.V. (2006). Attitude as Predictor of Success in Online Training. In International Journal on E-Learning 5(4) (pp. 623-639).

  • 62. Robai A.P. and Jordan H.M. (2004). Blended Learning and Sense of Community: A Comparative Analysis with Traditional and Fully Online Graduate Courses. In International Review of Research in Open and Distance Learning 5(2).

  • 63. Romero M. and Usart M. (2012). Game Based Learning Time-on-Task and Learning Performance According to the Students’ Temporal Perspective. In Proceedings of the 6th European Conference on Games Based Learning (pp. 4-5).

  • 64. Romero M. and Barberà E. (2013). Identificación de las dificultades de regulación del tiempo de los estudiantes universitarios en formación a distancia. RED. In Revista de Educación a Distancia 38.

  • 65. Sangrà A. (2001). La calidad en las experiencias virtuales de educación superior Actas de la conferencia internacional sobre educación formación y nuevas tecnologías (pp. 614-625).

  • 66. Sangrà A. (2002). A New Learning Model for the Information and Knowledge Society: The case of the Universitat Oberta de Catalunya (UOC). In The international review of Research in Open and Distance Learning 2(2) (pp. 1-8).

  • 67. Schmidt J.T. and Werner C.H. (2007). Designing Online Instruction for Success: Future Oriented Motivation and Self-Regulation. In The Electronic Journal of e-learning 5(1) (pp. 69 -78).

  • 68. Siemens G. and Matheos K. (2012). Systemic changes in higher education. In Education 16(1).

  • 69. Simons J.; Vansteenkiste M.; Lens W. and Lacante M. (2004). Placing motivation and future time perspective theory in a temporal perspective. In Educational Psychology Review 16(2) (pp. 121-139).

  • 70. Sullivan P. (2001). Gender differences and the online classroom: Male and female college students evaluate their experiences. In Community College Journal of Research &Practice 25(10) (pp. 805-818).

  • 71. Sursock A. and Smidtt H. (2010). Trends 2010: A decade of change in European Higher Education.European University Association. ISBN: 9789078997177.

  • 72. Swan K.; Shea P.; Fredericksen E.; Pickett A.; Pelz W.; Maher G. et al. (2000). Building knowledge building communities: Consistency contact and communication in the virtual classroom. In Journal of Educational Computing Research 23(4) (pp. 359-383).

  • 73. Taniguchi H. and Kaufman G. (2005). Degree completion among nontraditional college students. In Social Science Quarterly 86(4) (pp. 912-927).

  • 74. Thomas E. and Quinn J. (2007). First generation entry into higher education. McGraw-Hill International.

  • 75. Van der Veen I. and Peetsma T. (2011). Motivated for leisure in the future: A personcentred longitudinal study in the lowest level of secondary education. In Learning and Individual Differences 21(2) (pp. 233-238).

  • 76. Varela O.E.; Cater J.J. and Michel N. (2012). Online learning in management education: an empirical study of the role of personality traits. In Journal of Computing in Higher Education 24(3) (pp. 209-225).

  • 77. Vermeulen L. and Schmidt H.G. (2008). Learning environments learning process academic outcomes and career success of university graduates. In Studies in Higher Education 33(4) (pp. 431-451).

  • 78. Volery T. and Lord D. (2000). Critical success factors in online education. In International Journal of Educational Management 14(5) (pp. 216 - 223).

  • 79. Wetterich N.C. and Melo M.R. (2007). Sociodemographic profile of undergraduate nursing students. In Rev Latino-am Enfermagem 15(3) (pp. 404-410).

  • 80. Yang F.Y. and Tsai C.C. (2008). Investigating university student preferences and beliefs about learning in the Web-based context. In Computers & Education 50(4) (pp. 1284-1303).

  • 81. Young A. and Norgard C. (2006). Assessing the quality of online courses from the students’ perspective. In The Internet and Higher Education 9(2) (pp. 107-115). doi:10.1016/j.iheduc.2006.03.001

  • 82. Yukselturk E.; Ozekes S. and Türel Y.K. (2014).Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program. In European Journal of Open Distance and E-Learning 17(1). Available online at: http://www.eurodl.org/index.php?p=current&article=616

  • 83. Zabel A. (1995). Correspondence course completion rates. PhD dissertation. Retrieved from https://repositories.tdl.org/ttu-ir/bitstream/handle/2346/16268/31295009342592.pdf [01/06/2014]

  • 84. Zimbardo P.G.; Keough K.A. and Boyd J.N. (1997). Present time perspective as a predictor of risky driving. In Personality and Individual Differences 23 (pp. 1007-1023).

  • 85. Zimbardo P.G. and Boyd J.N. (1999). Putting time into perspective: A valid reliable individual differences metric. In Journal of Personality and Social Psychology 77 (pp. 1271-1288)

  • 86. Žuvic-Butorac M.; Roncevic N.; Nemcanin D. and Nebic Z. (2011). Blended E-Learning in Higher Education: Research on Students’ Perspective. In Issues in Informing Science and Information Technology 8 (pp. 409-429).

Search
Journal information
Cited By
Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 264 73 3
PDF Downloads 126 49 4